Fundamental Dynamics, Predictability, and Uncertainty of Scientific Discovery and Advance
Principal Investigator: Dashun Wang, Northwestern University
Co-Investigators: Brian Uzzi (Northwestern University); Benjamin Jones (Northwestern University); Luis Amaral (Northwestern University); James A. Evans (University of Chicago); Santo Fortunato (Indiana University); Albert-Laszlo Barabasi (Northeastern University)
Years of Award: 2019-2024
Managing Service Agency: The Air Force Office of Scientific Research
Exponential growth in scientific research and increasing complexity in science and technology (S&T) have created unprecedented opportunities and challenges for understanding and managing the research and development (R&D) enterprise of the 21st Century. On one hand, scholarly big data offers insight to scientific production and reward at novel scales and finer resolution than previously possible. Tens of millions of grant proposals, preprints, white papers, research articles, and patents are now produced every year. This explosion of data has the potential to benefit scientists and decision makers who seek to identify the most promising ideas, individuals, and teams early in the scientific process. On the other hand, science and technology constitute a fundamentally complex system: inherently complicated, involving convoluted interactions between components, and predisposed to emergent and unexpected collective outcomes that thwart simplistic approaches to anticipate, model, and predict the future. These analytical challenges are compounded in today’s increasingly complex environment of research interdisciplinary and fiscal scarcity.
In order to tackle these challenges, and anticipate and respond to new opportunities, we propose a five-year program of basic research to establish a systematic, quantitative framework for understanding the fundamental dynamics, predictability, and uncertainty of scientific discovery and advance. Insights we discover will enable the DoD to better lead, manage, and advance R&D relevant to national security needs. A defining feature of our proposed program is its mechanistic approach, developing rich mathematical and computational models to unearth fundamental patterns underlying science and technology, armed with big data and digital traces sampling from all phases of scientific production and use. Our interdisciplinary team brings together world-class thought leaders in the emerging research area of Science of Science. We aim to tackle these challenges with three cohesive research tasks that probe three critical, interconnected pillars of scientific discovery: ideas, individuals, and teams. By combining our diverse experience and approaches, results from this program will lead to punctuated advances in the way that knowledge is discovered, science is funded, scientists are trained and nurtured, excellence is recognized and rewarded, and failure is exploited and avoided.